Article ; Online: Understanding the pathophysiological changes via untargeted metabolomics in COVID-19 patients.
2020 Volume 93, Issue 4, Page(s) 2340–2349
Abstract: Coronavirus disease 2019 (COVID-19) is an infectious respiratory disease caused by a new strain of the coronavirus. There is limited data on the pathogenesis and the cellular responses of COVID-19. In this study, we aimed to determine the variation of ... ...
Abstract | Coronavirus disease 2019 (COVID-19) is an infectious respiratory disease caused by a new strain of the coronavirus. There is limited data on the pathogenesis and the cellular responses of COVID-19. In this study, we aimed to determine the variation of metabolites between healthy control and COVID-19 via the untargeted metabolomics method. Serum samples were obtained from 44 COVID-19 patients and 41 healthy controls. Untargeted metabolomics analyses were performed by the LC/Q-TOF/MS (liquid chromatography quadrupole time-of-flight mass spectrometry) method. Data acquisition, classification, and identification were achieved by the METLIN database and XCMS. Significant differences were determined between patients and healthy controls in terms of purine, glutamine, leukotriene D4 (LTD4), and glutathione metabolisms. Downregulations were determined in R-S lactoglutathione and glutamine. Upregulations were detected in hypoxanthine, inosine, and LTD4. Identified metabolites indicate roles for purine, glutamine, LTD4, and glutathione metabolisms in the pathogenesis of the COVID-19. The use of selective leukotriene D4 receptor antagonists, targeting purinergic signaling as a therapeutic approach and glutamine supplementation may decrease the severity and mortality of COVID-19. |
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MeSH term(s) | Adult ; Aged ; COVID-19/metabolism ; COVID-19/pathology ; COVID-19/virology ; Chromatography, Liquid/methods ; Databases, Factual ; Female ; Humans ; Male ; Metabolome ; Metabolomics/methods ; Middle Aged ; Prospective Studies ; ROC Curve ; SARS-CoV-2/isolation & purification ; Tandem Mass Spectrometry/methods |
Language | English |
Publishing date | 2020-12-17 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 752392-0 |
ISSN | 1096-9071 ; 0146-6615 |
ISSN (online) | 1096-9071 |
ISSN | 0146-6615 |
DOI | 10.1002/jmv.26716 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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